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An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device
[Nonparametric Option Pricing under Shape Restrictions]

Author

Listed:
  • Francesco Audrino
  • Robert Huitema
  • Markus Ludwig

Abstract

Building on the method of Ludwig (2015) to construct robust state price density surfaces from snapshots of option prices, we develop a nonparametric estimation strategy based on the recovery theorem of Ross (2015). Using options on the S&P 500, we then investigate whether or not recovery yields predictive information beyond what can be gleaned from risk-neutral densities. Over the 13 year period from 2000 to 2012, we find that market timing strategies based on recovered moments outperform those based on risk-neutral moments.

Suggested Citation

  • Francesco Audrino & Robert Huitema & Markus Ludwig, 2021. "An Empirical Implementation of the Ross Recovery Theorem as a Prediction Device [Nonparametric Option Pricing under Shape Restrictions]," Journal of Financial Econometrics, Oxford University Press, vol. 19(2), pages 291-312.
    • Handle: RePEc:oup:jfinec:v:19:y:2021:i:2:p:291-312.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbz002
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    More about this item

    Keywords

    predictive information; pricing kernel; risk-neutral density; Ross recovery theorem;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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